{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "60d8f9a9-f454-47af-aae3-76ae45fa42a8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 导入包\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8b83f603-4399-45ed-a98f-45feefc960fd",
   "metadata": {},
   "source": [
    "## Seaborn的调色盘\n",
    "\n",
    "#### 重点\n",
    "Seaborn提供了3种调色盘：\n",
    "* 定性调色盘：关联性不强的一组颜色，适合数据关联性不强，比较离散的情况（例如，分类）\n",
    "* 连续调色盘：同一色系不同饱和度，适合表示\n",
    "* 发散调色盘：中间颜色较浅，往两个方向逐渐加深\n",
    "\n",
    "1. 定性调色盘有5种调色盘系统：\n",
    "    1. 默认调色盘系统\n",
    "    2. hls调色盘系统\n",
    "    3. 分类调色盘系统\n",
    "    4. xkcd调色盘系统\n",
    "    5. 自定义调色盘系统"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "902eeefb-f4ca-4b95-8b61-4e7a409c19dd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>method</th>\n",
       "      <th>number</th>\n",
       "      <th>orbital_period</th>\n",
       "      <th>mass</th>\n",
       "      <th>distance</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Radial Velocity</td>\n",
       "      <td>1</td>\n",
       "      <td>269.300</td>\n",
       "      <td>7.10</td>\n",
       "      <td>77.40</td>\n",
       "      <td>2006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Radial Velocity</td>\n",
       "      <td>1</td>\n",
       "      <td>874.774</td>\n",
       "      <td>2.21</td>\n",
       "      <td>56.95</td>\n",
       "      <td>2008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Radial Velocity</td>\n",
       "      <td>1</td>\n",
       "      <td>763.000</td>\n",
       "      <td>2.60</td>\n",
       "      <td>19.84</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Radial Velocity</td>\n",
       "      <td>1</td>\n",
       "      <td>326.030</td>\n",
       "      <td>19.40</td>\n",
       "      <td>110.62</td>\n",
       "      <td>2007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Radial Velocity</td>\n",
       "      <td>1</td>\n",
       "      <td>516.220</td>\n",
       "      <td>10.50</td>\n",
       "      <td>119.47</td>\n",
       "      <td>2009</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            method  number  orbital_period   mass  distance  year\n",
       "0  Radial Velocity       1         269.300   7.10     77.40  2006\n",
       "1  Radial Velocity       1         874.774   2.21     56.95  2008\n",
       "2  Radial Velocity       1         763.000   2.60     19.84  2011\n",
       "3  Radial Velocity       1         326.030  19.40    110.62  2007\n",
       "4  Radial Velocity       1         516.220  10.50    119.47  2009"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 读取数据(seaborn提供测试数据)\n",
    "planets = pd.read_csv(\"dataset/planets.csv\")\n",
    "# 查看数据\n",
    "planets.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5857fc46-aebd-4efc-bb10-ffd14182a405",
   "metadata": {},
   "source": [
    "#### 调色盘的基本调用方法"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "1e2f253e-f6a6-4b45-87b0-8b122bdf840a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='year', ylabel='distance'>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 通过palette参数来设置绘图函数的调色盘\n",
    "    # 例如，绘制条形图时，不指定则会使用默认调色盘\n",
    "    # errorbar=None不显示置信区间\n",
    "sns.barplot(data=planets, x=\"year\", y=\"distance\", errorbar=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "0a026881-db9d-4f30-88b9-9f26fbe02566",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='year', ylabel='distance'>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 通过palette参数来设置绘图函数的调色盘\n",
    "    # 例如，绘制条形图时，指定调色盘\n",
    "        # palette=sns.color_palette(\"hls\")\n",
    "    # errorbar=None不显示置信区间\n",
    "        \n",
    "sns.barplot(data=planets, x=\"year\", y=\"distance\", errorbar=None, palette=sns.color_palette(\"hls\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "ce87f658-af4a-4922-a8be-112d263bddf1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1000x100 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 获取调色盘\n",
    "currentPalette = sns.color_palette()\n",
    "# 可视化调色盘\n",
    "    # 默认情况下调色盘上会有10个没有关联性的颜色\n",
    "sns.palplot(currentPalette)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "fb448e28-924b-4016-9cfe-5e685b3a0629",
   "metadata": {},
   "source": [
    "### 1. 定性调色盘\n",
    "\n",
    "#### 1.1 默认调色盘系统\n",
    "\n",
    "默认调色盘系统有6种风格：\n",
    "`deep`、`muted`、`pastel`、`bright`、`dark`、`colorblind`\n",
    "\n",
    "这6种风格的颜色不变，区别在于亮度和饱和度"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "3ec326aa-6228-4918-88e1-56ea4347d949",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1000x100 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# dark风格\n",
    "sns.palplot(sns.color_palette(\"dark\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "6d55ee62-9690-46c1-87f2-d85f9ca7900a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1000x100 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# bright风格\n",
    "sns.palplot(sns.color_palette(\"bright\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "be5a9b07-0efc-41cf-95fa-58211cfbb812",
   "metadata": {},
   "source": [
    "#### 1.2 hls调色盘系统\n",
    "通过颜色偏移产生多个颜色形成一个闭环，默认只产生6种颜色"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "8e06389f-8b25-4f78-8564-dc3f007c730c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 600x100 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.palplot(sns.color_palette(\"hls\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "7a4f843a-4174-41ff-ae66-6f8c0f171b47",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAEj4AAABlCAYAAADjEi16AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8pXeV/AAAACXBIWXMAAA9hAAAPYQGoP6dpAAAM1ElEQVR4nO3cTW4c1xmF4cuGKeZHJAENCXErXkFmWZBWFGTiFWQpIsCZJmo5tsxEnZEcZEL3OY6+QknPMyaMi9dFil1XOhen0+m0AAAAAAAAAAAAAAAAAAAAAAAABhy2PgAAAAAAAAAAAAAAAAAAAAAAAPDtMHwEAAAAAAAAAAAAAAAAAAAAAACMMXwEAAAAAAAAAAAAAAAAAAAAAACMMXwEAAAAAAAAAAAAAAAAAAAAAACMMXwEAAAAAAAAAAAAAAAAAAAAAACMMXwEAAAAAAAAAAAAAAAAAAAAAACMMXwEAAAAAAAAAAAAAAAAAAAAAACM+e6cL/r06dN6fHxc19fX6+Li4kufCQAAAAAAAAAAAAAAAAAAAAAA2JHT6bSOx+O6u7tbh8Ph2a89a/jo8fFx3d/f/18OBwAAAAAAAAAAAAAAAAAAAAAAfJ0eHh7W69evn/2as4aPrq+v11pr/eOvf1kvLy9//8m+FddbH2CndMu93PoAO6VbzvdnR7ec78+OZy3nWat89JEg9mHrA+zU+60PsEOetY5uOc06fq7lPGsd3XLHrQ+wU0/rausj7JAP7x3dcl56dHTL+f7s6Jbz/dnxrOU8axUXBzkf3jtesOU8ax3dcpp1/FzLedY6uuVcHFSunrY+wf745N7RLeeNR0e3nO/Pjm45358dz1rOs9a5XB+3PsIO+fDe8YIt51nr6JbTrOPnWs6z1tEt5+Ig9eHpaX3/w99/3St6zlnDRxcXF2uttV5eXq7rF/6y0tlebH2AnfJvZXJ/2PoAO/XHrQ+wQ5p1/rT1AXboz1sfYKd0y7mJqFz6PTd22voAO/XvrQ+wQ5+2PsBOedZy/9r6ADv1y9YH2CF/N7rjWcv5FbelXE6zjouDnIuDjpfgOc06Lg5yXoB3dMu5OKi4OMi5OOh4mZtzcdDxrOVcHHS8zM25OOh41nJ+xa3IltOs49Yg59ag4w14TrOOW4Oct98d3XJuDTovln+DnHNx0PEyN+fioONZy7k46HiZm3Nx0PGs5bzNbX3eK3rOYeAcAAAAAAAAAAAAAAAAAAAAAAAAay3DRwAAAAAAAAAAAAAAAAAAAAAAwCDDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwBjDRwAAAAAAAAAAAAAAAAAAAAAAwJjvzvmi0+m01lrrw9PTFz3MV+eXrQ+wUx+3PsAOXW59gJ066ycg/0Ozjm4504wd3XIXWx9gnz763SP249YH2Cndcv/c+gA79dPWB9ihn7c+wE7plvOaqOO1ZE6zzpMPogVPW8efCDkf3jte5uY06+iW83tHR7eci4OKi4OcF+Ad3XIuDjouDnJegHd0y3lN1PFaMqdZ5eCfGsQ8ah1/HOR8cu94k5vTrKNbztvvjm45twadS7+xFbwA7+iWc3HQcXGQ8wK8o1vO7x0dbyZzmqU+7xN93it6zlnvRt69e7fWWuv7v/3wO44FAAAAAAAAAAAAAAAAAAAAAAB8zY7H47q9vX32a84aPnr16tVaa623b9/+5n+Q/3r//v26v79fDw8P6+bmZuvj7IJmHd1ymnV0y2nW0S2nWUe3nGYd3XKadXTLadbRLadZR7ecZh3dcpp1dMtp1tEtp1lHt5xmHd1ymnV0y2nW0S2nWUe3nGYd3XKadXTLadbRLadZR7ecZh3dcpp1dMtp1tEtp1lHt5xmHd1ymnV0y2nW0S2nWUe3nGYd3XKn02kdj8d1d3f3m1971vDR4XBYa611e3vrf0Lh5uZGt5BmHd1ymnV0y2nW0S2nWUe3nGYd3XKadXTLadbRLadZR7ecZh3dcpp1dMtp1tEtp1lHt5xmHd1ymnV0y2nW0S2nWUe3nGYd3XKadXTLadbRLadZR7ecZh3dcpp1dMtp1tEtp1lHt5xmHd1ymnV0y2nW0S2nWUe3nGYd3TK3t7dnfd3hC58DAAAAAAAAAAAAAAAAAAAAAADgV4aPAAAAAAAAAAAAAAAAAAAAAACAMWcNH11dXa03b96sq6urL32er4puOc06uuU06+iW06yjW06zjm45zTq65TTr6JbTrKNbTrOObjnNOrrlNOvoltOso1tOs45uOc06uuU06+iW06yjW06zjm45zTq65TTr6JbTrKNbTrOObjnNOrrlNOvoltOso1tOs45uOc06uuU06+iW06yjW06zjm45zTq6fVkXp9PptPUhAAAAAAAAAAAAAAAAAAAAAACAb8Nh6wMAAAAAAAAAAAAAAAAAAAAAAADfDsNHAAAAAAAAAAAAAAAAAAAAAADAGMNHAAAAAAAAAAAAAAAAAAAAAADAGMNHAAAAAAAAAAAAAAAAAAAAAADAGMNHAAAAAAAAAAAAAAAAAAAAAADAGMNHAAAAAAAAAAAAAAAAAAAAAADAGMNHAAAAAAAAAAAAAAAAAAAAAADAGMNHAAAAAAAAAAAAAAAAAAAAAADAmP8AMLN08d3bjHcAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 6000x100 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.palplot(sns.color_palette(\"hls\", n_colors=60))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "19f2ac2d-492e-462f-ba09-774e2815f9d0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 600x100 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# sns.hls_palette()函数的功能更加强大，可以设定调色盘的起始颜色、亮度、饱和度\n",
    "    # h：起始颜色\n",
    "    # l：亮度\n",
    "    # s：饱和度\n",
    "sns.palplot(sns.hls_palette(h=0.2, l=0.4, s=0.5))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "4f04f8d7-10e3-435f-b95f-29ae7b0389c8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1000x100 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# sns.hls_palette()函数的功能更加强大，可以设定调色盘的起始颜色、亮度、饱和度\n",
    "    # h：起始颜色\n",
    "    # l：亮度\n",
    "    # s：饱和度\n",
    "sns.palplot(sns.hls_palette(n_colors=10, h=0.2, l=0.8, s=0.5))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f07b0ca8-9e7e-4340-a965-0f462c49958d",
   "metadata": {},
   "source": [
    "#### 1.3 分类调色盘系统\n",
    "Searborn设定好了分组颜色的调色盘系统"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "8affdd2a-7f4e-4bdd-9dc5-4658e2516fef",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1200x100 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.palplot(sns.color_palette(\"Paired\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "425c1a0c-fe92-49a0-80a8-ba970625b0cc",
   "metadata": {},
   "source": [
    "#### 1.4 xkcd调色盘系统\n",
    "Searborn也支持xkcd提供954种预调色，参见https://xkcd.com/color/rgb/\n",
    "可以直接选用xkcd颜色组成调色盘"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "7f6a9e07-bc83-4009-a226-849167a2a1f5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 500x100 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 自选xkcd颜色\n",
    "myColors = [\n",
    "    \"light blue\",\n",
    "    \"maroon\",\n",
    "    \"beige\",\n",
    "    \"lilac\",\n",
    "    \"salmon\"\n",
    "]\n",
    "sns.palplot(sns.xkcd_palette(myColors))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0a498c60-9dfd-4aa1-b24a-e7cc4fe23c36",
   "metadata": {},
   "source": [
    "#### 1.5 自定义调色盘系统\n",
    "Searborn也支持使用16进制自定义调色"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "89b94a2c-a929-4e48-ae04-eaaeeacfcf4e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 500x100 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 自定义颜色\n",
    "myColors2 = [\n",
    "    \"#653700\",\n",
    "    \"#9aae07\",\n",
    "    \"#ffcfdc\",\n",
    "    \"#c04e01\",\n",
    "    \"#380282\"\n",
    "]\n",
    "sns.palplot(sns.color_palette(myColors2))"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "91ece70d-eb8a-475d-afd4-339b7a98624b",
   "metadata": {},
   "source": [
    "### 2. 连续调色盘\n",
    "\n",
    "连续调色盘会根据指定的色系自动进行颜色深浅的过度，默认情况下是由浅入深\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "d1a9e344-3264-45ad-b5b3-72add86916aa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 600x100 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 例如，指定蓝色系\n",
    "    # 默认情况下是由浅入深\n",
    "    # 注意，首字母大写，而且要带复数\n",
    "sns.palplot(sns.color_palette(\"Blues\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "cd2c35b1-f6c8-4128-9f02-b2c118f12b27",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 600x100 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 色系以”_r“结尾代表深浅方向翻转\n",
    "sns.palplot(sns.color_palette(\"Blues_r\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "8700952e-e6f5-4da6-b647-717a502a4800",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 600x100 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.palplot(sns.color_palette(\"Reds\"))"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "d3e5b946-7282-4bdb-8dc5-59465958d87d",
   "metadata": {},
   "source": [
    "### 3. 发散调色盘\n",
    "\n",
    "发散调色盘会根据指定的值排序自动进行发散颜色的显式\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "ef60cfbd-0a3c-4207-ae1a-b31f7b83b5da",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "values = [13, 32, 12, 43, -23, -32]\n",
    "with sns.color_palette(\"RdBu\"):\n",
    "    sns.barplot(x=list(range(0, 6)), y=sorted(values))"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
